Computational Physics Section of the American Journal of Physics
Jan Tobochnik and Harvey Gould, editors

Information about the Computational Physics Section is available at Jan Tobochnik and Harvey Gould, “New Computational Physics Section,” Am. J. Phys. 80, 1041 (2012). We welcome your submissions and suggestions.

  1. K. Binder, B. J. Block, P. Virnau, and A. Tröster, “Beyond the Van Der Waals loop: What can be learned from simulating Lennard-Jones fluids inside the region of phase coexistence,” Am. J. Phys. 80, 1099–1109 (2012).
  2. G. Volpe and G. Volpe, “Simulation of a Brownian particle in an optical trap,” Am. J. Phys. 81, 224–230 (2013).
  3. F. J. Vesely, “Of pendulums, polymers and robots: Computational mechanics with constraints,” Am. J. Phys. 81, 537–544 (2013).
  4. M. Patriarca and A. Chakraborti, “Kinetic exchange models: From molecular physics to social science,” Am. J. Phys. 81, 618–623 (2013).
  5. R. H. Swendsen, “Using computation to teach the properties of the van der Waals fluid,” Am. J. Phys. 81, 776–781 (2013).
  6. T. Price and R. H. Swendsen, “Numerical computation for teaching quantum statistics,” Am. J. Phys. 81, 866–872 (2013).
  7. Robert M. Dimeo, “Wave packet scattering from time-varying potential barriers in one dimension,” Am. J. Phys. 82, 142–152 (2014).
  8. Milovan Suvakov and V. Dmitravsinovic, “A guide to hunting periodic three-body orbits,” Am. J. Phys. 82, 609–619 (2014).
  9. Tao Pang, “Diffusion Monte Carlo: A powerful tool for studying quantum many-body systems,” Am. J. Phys. 82, 980–988 (2014).
  10. Adriana Gomes Dickman and Ronald Dickman, “Computational model of a vector-mediated epidemic,” Am. J. Phys. 83, 468–474 (2015).
  11. Fernando M. S. Silva Fernandes, “Gibbs ensemble Monte Carlo,” Am. J. Phys. 83, 809–816 (2015).
  12. Larry Engelhardt, “Magnetic resonance: Using computer simulations and visualizations to connect quantum theory with classical concepts,” Am. J. Phys. 83, 1051–1056 (2015).
  13. L. L. Iannini and Ronald Dickman, “Kinetic theory of vehicular traffic,” Am. J. Phys. 84, 135–145 (2016).
  14. Christian G. Fink, “Simulating synchronization in neuronal networks,” Am. J. Phys. 84, 467–473 (2016).
  15. Yanyan Claire Ji and Flavio H. Fenton, “Numerical solutions of reaction-diffusion equations: Application to neural and cardiac models,” Am. J. Phys. 84, 626–638 (2016).
  16. William Graham Hoover, Julien Clinton Sprott, and Carol Griswold Hoover, “Adaptive Runge-Kutta integration for stiff systems: Comparing Nosé and Nosé-Hoover dynamics for the harmonic oscillator,” Am. J. Phys. 84, 786–794 (2016).
  17. Marija Vucelja, “Lifting -- A nonreversible Markov chain Monte Carlo algorithm,” Am. J. Phys. 84, 958–968 (2016).
  18. Yu Liu, Chao Li, Huai-Yu Wang, and Yun-Song Zhou, “The generalized scattering coefficient method for plane wave scattering in layered structures,” Am. J. Phys. 85, 146–150 (2017).
  19. Daniel V. Schroeder, “The variational-relaxation algorithm for finding quantum bound states,” Am. J. Phys. 85, 698–704 (2017).
  20. J. Wang and Y. Hao, “Meshfree computation of electrostatics and related boundary value problems,” Am. J. Phys. 85, 542–549 (2017.
  21. F. Esquembre, W. Christian, and M. Belloni, “Parallel programming with Easy Java Simulations,” Am. J. Phys. 86, 54–67 (2018).
  22. Marise J. E. Westbroek, Peter R. King, Dimitri D. Vvedensky, and Stephan Dürr, “User's guide to Monte Carlo methods for evaluating path integrals,” Am. J. Phys. 86, 293–304 (2018).
  23. Ge Zhang, “Random sequential adsorption and its long-time limit,” to be published.

Updated 6 August 2018.